Overview

Dataset statistics

Number of variables10
Number of observations310
Missing cells247
Missing cells (%)8.0%
Duplicate rows16
Duplicate rows (%)5.2%
Total size in memory26.2 KiB
Average record size in memory86.4 B

Variable types

Categorical5
Numeric4
Text1

Dataset

Description충청북도 단양군 산림정밀지도db 데이터로 지적코드, 조림 기타주소, 시행시작일, 시행종료일, 면적, 읍면동명, 리명, 군유림 여부, 면적, 데이터기준일자 등의 데이터 포함
Author충청북도 단양군
URLhttps://www.data.go.kr/data/15089397/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
Dataset has 16 (5.2%) duplicate rowsDuplicates
읍면동명 is highly overall correlated with 지적코드High correlation
지적코드 is highly overall correlated with 군유지_면적 and 2 other fieldsHigh correlation
조림_시행시작일 is highly overall correlated with 조림_시행종료일High correlation
조림_시행종료일 is highly overall correlated with 조림_시행시작일High correlation
군유지_면적 is highly overall correlated with 면적 and 3 other fieldsHigh correlation
면적 is highly overall correlated with 군유지_면적 and 1 other fieldsHigh correlation
조림_기타주소 is highly overall correlated with 군유지_면적 and 2 other fieldsHigh correlation
군유림여부 is highly overall correlated with 군유지_면적High correlation
조림_기타주소 is highly imbalanced (68.7%)Imbalance
군유지_면적 has 247 (79.7%) missing valuesMissing

Reproduction

Analysis started2024-04-17 11:02:02.926237
Analysis finished2024-04-17 11:02:04.578529
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지적코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
4380030000000000000
235 
4380040000000000000
75 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4380030000000000000
2nd row4380030000000000000
3rd row4380030000000000000
4th row4380030000000000000
5th row4380030000000000000

Common Values

ValueCountFrequency (%)
4380030000000000000 235
75.8%
4380040000000000000 75
 
24.2%

Length

2024-04-17T20:02:04.629374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:02:04.706230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4380030000000000000 235
75.8%
4380040000000000000 75
 
24.2%

조림_기타주소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
259 
외 1필지
 
10
외 5필지
 
8
외 2필지
 
7
외 4필지
 
6
Other values (9)
 
20

Length

Max length6
Median length4
Mean length4.1548387
Min length2

Unique

Unique4 ?
Unique (%)1.3%

Sample

1st row외 4필지
2nd row외 4필지
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 259
83.5%
외 1필지 10
 
3.2%
외 5필지 8
 
2.6%
외 2필지 7
 
2.3%
외 4필지 6
 
1.9%
외 3필지 5
 
1.6%
외1 3
 
1.0%
외 15필지 3
 
1.0%
외 18필지 3
 
1.0%
외 6필지 2
 
0.6%
Other values (4) 4
 
1.3%

Length

2024-04-17T20:02:04.795651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 259
72.5%
외 47
 
13.2%
1필지 10
 
2.8%
5필지 8
 
2.2%
2필지 7
 
2.0%
4필지 6
 
1.7%
3필지 5
 
1.4%
외1 3
 
0.8%
15필지 3
 
0.8%
18필지 3
 
0.8%
Other values (5) 6
 
1.7%

조림_시행시작일
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20018583
Minimum20000000
Maximum20070000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-17T20:02:04.887063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000000
5-th percentile20000000
Q120000403
median20010414
Q320030227
95-th percentile20055500
Maximum20070000
Range70000
Interquartile range (IQR)29824

Descriptive statistics

Standard deviation17939.5
Coefficient of variation (CV)0.00089614238
Kurtosis0.44934642
Mean20018583
Median Absolute Deviation (MAD)10083
Skewness1.0712539
Sum6.2057606 × 109
Variance3.2182568 × 108
MonotonicityNot monotonic
2024-04-17T20:02:04.978333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20020311 46
14.8%
20010000 45
14.5%
20000000 34
11.0%
20010414 27
8.7%
20030227 26
8.4%
20000316 26
8.4%
20050000 20
6.5%
20040305 19
6.1%
20020000 14
 
4.5%
20010302 13
 
4.2%
Other values (6) 40
12.9%
ValueCountFrequency (%)
20000000 34
11.0%
20000313 9
 
2.9%
20000316 26
8.4%
20000331 5
 
1.6%
20000403 6
 
1.9%
20010000 45
14.5%
20010302 13
 
4.2%
20010414 27
8.7%
20020000 14
 
4.5%
20020311 46
14.8%
ValueCountFrequency (%)
20070000 7
 
2.3%
20060000 9
 
2.9%
20050000 20
6.5%
20040305 19
6.1%
20030227 26
8.4%
20021109 4
 
1.3%
20020311 46
14.8%
20020000 14
 
4.5%
20010414 27
8.7%
20010302 13
 
4.2%

조림_시행종료일
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20018721
Minimum20000000
Maximum20070000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-17T20:02:05.068673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000000
5-th percentile20000000
Q120000523
median20010618
Q320030520
95-th percentile20055500
Maximum20070000
Range70000
Interquartile range (IQR)29997

Descriptive statistics

Standard deviation17935.83
Coefficient of variation (CV)0.00089595282
Kurtosis0.41854649
Mean20018721
Median Absolute Deviation (MAD)10095
Skewness1.0593689
Sum6.2058036 × 109
Variance3.2169398 × 108
MonotonicityNot monotonic
2024-04-17T20:02:05.159331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
20020624 46
14.8%
20010000 45
14.5%
20000000 34
11.0%
20010618 27
8.7%
20030520 26
8.4%
20000508 23
7.4%
20050000 20
6.5%
20040515 19
6.1%
20000523 17
 
5.5%
20020000 14
 
4.5%
Other values (5) 39
12.6%
ValueCountFrequency (%)
20000000 34
11.0%
20000501 6
 
1.9%
20000508 23
7.4%
20000523 17
 
5.5%
20010000 45
14.5%
20010521 13
 
4.2%
20010618 27
8.7%
20020000 14
 
4.5%
20020624 46
14.8%
20021130 4
 
1.3%
ValueCountFrequency (%)
20070000 7
 
2.3%
20060000 9
 
2.9%
20050000 20
6.5%
20040515 19
6.1%
20030520 26
8.4%
20021130 4
 
1.3%
20020624 46
14.8%
20020000 14
 
4.5%
20010618 27
8.7%
20010521 13
 
4.2%

군유지_면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct47
Distinct (%)74.6%
Missing247
Missing (%)79.7%
Infinite0
Infinite (%)0.0%
Mean211958.24
Minimum3787
Maximum993143
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-17T20:02:05.267804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3787
5-th percentile7537
Q153801.5
median126576
Q3222545
95-th percentile824165.5
Maximum993143
Range989356
Interquartile range (IQR)168743.5

Descriptive statistics

Standard deviation260922.15
Coefficient of variation (CV)1.2310074
Kurtosis2.7767707
Mean211958.24
Median Absolute Deviation (MAD)87204
Skewness1.9087943
Sum13353369
Variance6.8080369 × 1010
MonotonicityNot monotonic
2024-04-17T20:02:05.377523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
993143 3
 
1.0%
78545 3
 
1.0%
30683 3
 
1.0%
152137 2
 
0.6%
132893 2
 
0.6%
7537 2
 
0.6%
53950 2
 
0.6%
169388 2
 
0.6%
239008 2
 
0.6%
126149 2
 
0.6%
Other values (37) 40
 
12.9%
(Missing) 247
79.7%
ValueCountFrequency (%)
3787 2
0.6%
3806 1
 
0.3%
7537 2
0.6%
10711 1
 
0.3%
12344 1
 
0.3%
25785 1
 
0.3%
28562 1
 
0.3%
30683 3
1.0%
34116 1
 
0.3%
39372 1
 
0.3%
ValueCountFrequency (%)
993143 3
1.0%
833851 1
 
0.3%
736996 1
 
0.3%
733033 1
 
0.3%
699586 1
 
0.3%
664755 1
 
0.3%
439877 1
 
0.3%
366942 1
 
0.3%
356628 1
 
0.3%
356007 1
 
0.3%

읍면동명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
매포읍
55 
단성면
48 
영춘면
47 
단양읍
46 
어상천면
42 
Other values (3)
72 

Length

Max length4
Median length3
Mean length3.1354839
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단양읍
2nd row단양읍
3rd row단양읍
4th row단양읍
5th row단양읍

Common Values

ValueCountFrequency (%)
매포읍 55
17.7%
단성면 48
15.5%
영춘면 47
15.2%
단양읍 46
14.8%
어상천면 42
13.5%
가곡면 29
9.4%
적성면 27
8.7%
대강면 16
 
5.2%

Length

2024-04-17T20:02:05.493766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:02:05.587083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매포읍 55
17.7%
단성면 48
15.5%
영춘면 47
15.2%
단양읍 46
14.8%
어상천면 42
13.5%
가곡면 29
9.4%
적성면 27
8.7%
대강면 16
 
5.2%

리명
Text

Distinct64
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-17T20:02:05.768565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0645161
Min length2

Characters and Unicode

Total characters950
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)4.5%

Sample

1st row별곡리
2nd row별곡리
3rd row별곡리
4th row별곡리
5th row별곡리
ValueCountFrequency (%)
오사리 20
 
6.5%
임현리 15
 
4.8%
가평리 15
 
4.8%
삼곡리 14
 
4.5%
노동리 13
 
4.2%
연곡리 12
 
3.9%
파랑리 12
 
3.9%
기촌리 10
 
3.2%
상진리 10
 
3.2%
외중방리 10
 
3.2%
Other values (54) 179
57.7%
2024-04-17T20:02:06.073634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 310
32.6%
곡 53
 
5.6%
사 32
 
3.4%
평 27
 
2.8%
가 21
 
2.2%
대 21
 
2.2%
방 21
 
2.2%
오 20
 
2.1%
상 20
 
2.1%
하 18
 
1.9%
Other values (63) 407
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 950
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 310
32.6%
곡 53
 
5.6%
사 32
 
3.4%
평 27
 
2.8%
가 21
 
2.2%
대 21
 
2.2%
방 21
 
2.2%
오 20
 
2.1%
상 20
 
2.1%
하 18
 
1.9%
Other values (63) 407
42.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 950
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 310
32.6%
곡 53
 
5.6%
사 32
 
3.4%
평 27
 
2.8%
가 21
 
2.2%
대 21
 
2.2%
방 21
 
2.2%
오 20
 
2.1%
상 20
 
2.1%
하 18
 
1.9%
Other values (63) 407
42.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 950
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 310
32.6%
곡 53
 
5.6%
사 32
 
3.4%
평 27
 
2.8%
가 21
 
2.2%
대 21
 
2.2%
방 21
 
2.2%
오 20
 
2.1%
상 20
 
2.1%
하 18
 
1.9%
Other values (63) 407
42.8%

군유림여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
247 
1
63 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 247
79.7%
1 63
 
20.3%

Length

2024-04-17T20:02:06.173540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:02:06.247919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 247
79.7%
1 63
 
20.3%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct237
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140905.53
Minimum16
Maximum1662347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-17T20:02:06.330862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile464.6
Q19911.75
median42050
Q3120322.5
95-th percentile735212.65
Maximum1662347
Range1662331
Interquartile range (IQR)110410.75

Descriptive statistics

Standard deviation288840.41
Coefficient of variation (CV)2.0498869
Kurtosis12.207562
Mean140905.53
Median Absolute Deviation (MAD)37399.5
Skewness3.4707663
Sum43680715
Variance8.342878 × 1010
MonotonicityNot monotonic
2024-04-17T20:02:06.443462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6974.0 5
 
1.6%
25504.0 5
 
1.6%
318347.0 4
 
1.3%
405144.0 4
 
1.3%
7934.0 3
 
1.0%
993143.0 3
 
1.0%
53950.0 3
 
1.0%
1335130.0 3
 
1.0%
1232132.0 3
 
1.0%
206130.0 3
 
1.0%
Other values (227) 274
88.4%
ValueCountFrequency (%)
16.0 1
0.3%
50.0 1
0.3%
53.0 1
0.3%
62.0 1
0.3%
106.0 1
0.3%
162.0 2
0.6%
235.0 1
0.3%
298.0 1
0.3%
325.0 1
0.3%
366.0 1
0.3%
ValueCountFrequency (%)
1662347.0 2
0.6%
1442631.0 3
1.0%
1335130.0 3
1.0%
1232132.0 3
1.0%
993143.0 3
1.0%
833851.0 1
 
0.3%
736996.0 1
 
0.3%
733033.0 1
 
0.3%
699586.0 1
 
0.3%
682113.0 1
 
0.3%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2022-09-25
310 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-25
2nd row2022-09-25
3rd row2022-09-25
4th row2022-09-25
5th row2022-09-25

Common Values

ValueCountFrequency (%)
2022-09-25 310
100.0%

Length

2024-04-17T20:02:06.543409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:02:06.614100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-25 310
100.0%

Interactions

2024-04-17T20:02:04.118649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.274587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.564027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.853688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:04.192868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.351281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.636962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.926172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:04.267565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.425865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.714205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.996408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:04.333012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.492408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:03.784734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:02:04.057936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:02:06.665607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지적코드조림_기타주소조림_시행시작일조림_시행종료일군유지_면적읍면동명리명군유림여부면적
지적코드1.0000.7030.1110.1110.5451.0001.0000.2990.214
조림_기타주소0.7031.0000.6930.693NaN0.6310.9070.2180.895
조림_시행시작일0.1110.6931.0001.0000.3910.4600.8770.2670.200
조림_시행종료일0.1110.6931.0001.0000.3910.4600.8770.2670.200
군유지_면적0.545NaN0.3910.3911.0000.5970.909NaN0.997
읍면동명1.0000.6310.4600.4600.5971.0001.0000.3930.317
리명1.0000.9070.8770.8770.9091.0001.0000.5480.825
군유림여부0.2990.2180.2670.267NaN0.3930.5481.0000.356
면적0.2140.8950.2000.2000.9970.3170.8250.3561.000
2024-04-17T20:02:06.759524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조림_기타주소군유림여부읍면동명지적코드
조림_기타주소1.0000.1650.3200.585
군유림여부0.1651.0000.2920.193
읍면동명0.3200.2921.0000.990
지적코드0.5850.1930.9901.000
2024-04-17T20:02:06.834457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조림_시행시작일조림_시행종료일군유지_면적면적지적코드조림_기타주소읍면동명군유림여부
조림_시행시작일1.0000.9970.019-0.2080.1050.4460.2470.232
조림_시행종료일0.9971.0000.018-0.2090.1050.4460.2470.232
군유지_면적0.0190.0181.0001.0000.5181.0000.3411.000
면적-0.208-0.2091.0001.0000.2110.6870.1610.352
지적코드0.1050.1050.5180.2111.0000.5850.9900.193
조림_기타주소0.4460.4461.0000.6870.5851.0000.3200.165
읍면동명0.2470.2470.3410.1610.9900.3201.0000.292
군유림여부0.2320.2321.0000.3520.1930.1650.2921.000

Missing values

2024-04-17T20:02:04.426106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:02:04.535014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지적코드조림_기타주소조림_시행시작일조림_시행종료일군유지_면적읍면동명리명군유림여부면적데이터 기준일자
04380030000000000000외 4필지2000000020000000<NA>단양읍별곡리017326.02022-09-25
14380030000000000000외 4필지2000031620000523<NA>단양읍별곡리017326.02022-09-25
24380030000000000000<NA>2002031120020624<NA>단양읍별곡리07208.02022-09-25
34380030000000000000<NA>2002031120020624<NA>단양읍별곡리063109.02022-09-25
44380030000000000000<NA>2002031120020624<NA>단양읍별곡리032818.02022-09-25
54380030000000000000외 2필지20000000200000003787단양읍상진리13787.02022-09-25
64380030000000000000외 2필지20000316200005233787단양읍상진리13787.02022-09-25
74380030000000000000외 5필지2001030220010521<NA>단양읍상진리057818.02022-09-25
84380030000000000000<NA>2001000020010000<NA>단양읍상진리06678.02022-09-25
94380030000000000000외 5필지2001000020010000<NA>단양읍상진리06678.02022-09-25
지적코드조림_기타주소조림_시행시작일조림_시행종료일군유지_면적읍면동명리명군유림여부면적데이터 기준일자
3004380040000000000000<NA>2001030220010521<NA>단성면고평리090942.02022-09-25
3014380040000000000000<NA>2001041420010618<NA>단성면고평리0185614.02022-09-25
3024380040000000000000<NA>2001041420010618733033단성면양당리1733033.02022-09-25
3034380040000000000000<NA>2005000020050000<NA>단성면가산리02320.02022-09-25
3044380040000000000000<NA>2005000020050000<NA>단성면가산리01898.02022-09-25
3054380040000000000000<NA>2005000020050000<NA>단성면가산리0366.02022-09-25
3064380040000000000000<NA>2005000020050000<NA>단성면가산리0325.02022-09-25
3074380040000000000000<NA>2005000020050000<NA>단성면가산리02369.02022-09-25
3084380040000000000000<NA>2004030520040515110050단성면대잠리1110050.02022-09-25
3094380040000000000000<NA>2000040320000501<NA>단성면대잠리0143874.02022-09-25

Duplicate rows

Most frequently occurring

지적코드조림_기타주소조림_시행시작일조림_시행종료일군유지_면적읍면동명리명군유림여부면적데이터 기준일자# duplicates
14380030000000000000<NA>2000000020000000<NA>매포읍가평리01225.02022-09-253
34380030000000000000<NA>2000000020000000<NA>매포읍삼곡리0318347.02022-09-253
04380030000000000000외 1필지2000000020000000<NA>가곡면사평리0126891.02022-09-252
24380030000000000000<NA>2000000020000000<NA>매포읍삼곡리029622.02022-09-252
44380030000000000000<NA>2001000020010000<NA>가곡면향산리01442631.02022-09-252
54380030000000000000<NA>2001000020010000<NA>매포읍우덕리0461.02022-09-252
64380030000000000000<NA>2002000020020000<NA>매포읍우덕리07934.02022-09-252
74380030000000000000<NA>20020311200206247537어상천면대전리17537.02022-09-252
84380030000000000000<NA>2002031120020624<NA>매포읍영천리01662347.02022-09-252
94380030000000000000<NA>2003022720030520222545단양읍금곡리1222545.02022-09-252